tf.compat.v1.Print

Prints a list of tensors. (deprecated)

tf.compat.v1.Print(
    input_, data, message=None, first_n=None, summarize=None, name=None
)

Warning: THIS FUNCTION IS DEPRECATED. It will be removed after 2018-08-20. Instructions for updating: Use tf.print instead of tf.Print. Note that tf.print returns a no-output operator that directly prints the output. Outside of defuns or eager mode, this operator will not be executed unless it is directly specified in session.run or used as a control dependency for other operators. This is only a concern in graph mode. Below is an example of how to ensure tf.print executes in graph mode:

This is an identity op (behaves like tf.identity) with the side effect of printing data when evaluating.

Note: This op prints to the standard error. It is not currently compatible with jupyter notebook (printing to the notebook server's output, not into the notebook).

Additionally, to use tf.print in python 2.7, users must make sure to import the following:

from __future__ import print_function

Args:

input_: A tensor passed through this op.
data: A list of tensors to print out when op is evaluated.
message: A string, prefix of the error message.
first_n: Only log first_n number of times. Negative numbers log always; this is the default.
summarize: Only print this many entries of each tensor. If None, then a maximum of 3 elements are printed per input tensor.
name: A name for the operation (optional).

Returns:

A Tensor. Has the same type and contents as input_.

sess = tf.compat.v1.Session()
with sess.as_default():
    tensor = tf.range(10)
    print_op = tf.print(tensor)
    with tf.control_dependencies([print_op]):
      out = tf.add(tensor, tensor)
    sess.run(out)